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There is more than some fuzziness to the data! At some point, measuring something sufficiently poorly is worse than not measuring it at all, and the empirical e

There is more than some fuzziness to the data! At some point, measuring something sufficiently poorly is worse than not measuring it at all, and the empirical efforts I've seen to evaluate things I care about (programming languages, static types, etc) all fall into that category. The alternative is to rely on rich experience and good taste. If you want to make it a bit more rigorous, you can approach this in terms of qualitative research—which makes sense for academic research, but isn't necessarily the best way to learn for yourself or to design tools. Expert experience is far more effective at capturing complex, multi-dimensional phenomena than anything we can reduce to a small number of easily-gathered quantitative metrics.

itsoktocry 3y ago
>At some point, measuring something sufficiently poorly is worse than not measuring it at all At what point, and how do you determine that? >The alternative is to rely on rich experience and good taste. Everyone thinks they have good taste.
- worik 3y ago
  > Everyone thinks they have good taste. That is not true In a different domain I play music in bands I have played in a band where the band leader was so so at playing their instrument, but had oodles of taste, so much more than me Not all of us, not many of us, are arrogant pric,s who think we know better or are better than we are
- tikhonj 3y ago
  > At what point, and how do you determine that? By looking at the research? By understanding what kind of studies and experiments are actually viable? By evaluating what we can measure effectively, what we can't, and how good (or bad!) our proxy metrics can be? As a field, we really need to understand the inherent limits of quantitative methods.